96 research outputs found
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
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Wyner-Ziv side information generation using a higher order piecewise trajectory temporal interpolation algorithm
Distributed video coding (DVC) reverses the traditional coding paradigm of complex encoders allied with basic decoding, to one where the computational cost is largely incurred by the decoder. This enables low-cost, resource-poor sensors to be used at the transmitter in various applications including multi-sensor surveillance. A key constraint governing DVC performance is the quality of side information (SI), a coarse representation of original video frames which are not available at the decoder. Techniques to generate SI have generally been based on linear temporal interpolation, though these do not always produce satisfactory SI quality especially in sequences exhibiting asymmetric (non-linear) motion. This paper presents a higher-order piecewise trajectory temporal interpolation (HOPTTI) algorithm for SI generation that quantitatively and perceptually affords better SI quality in comparison to existing temporal interpolation-based approaches
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
The recently developed Distributed Video Coding (DVC) is typically suitable for the
applications where the conventional video coding is not feasible because of its
inherent high-complexity encoding. Examples include video surveillance usmg
wireless/wired video sensor network and applications using mobile cameras etc. With
DVC, the complexity is shifted from the encoder to the decoder.
The practical application of DVC is referred to as Wyner-Ziv video coding (WZ)
where an estimate of the original frame called "side information" is generated using
motion compensation at the decoder. The compression is achieved by sending only
that extra information that is needed to correct this estimation. An error-correcting
code is used with the assumption that the estimate is a noisy version of the original
frame and the rate needed is certain amount of the parity bits. The side information is
assumed to have become available at the decoder through a virtual channel. Due to
the limitation of compensation method, the predicted frame, or the side information, is
expected to have varying degrees of success. These limitations stem from locationspecific
non-stationary estimation noise. In order to avoid these, the conventional
video coders, like MPEG, make use of frame partitioning to allocate optimum coder
for each partition and hence achieve better rate-distortion performance. The same,
however, has not been used in DVC as it increases the encoder complexity.
This work proposes partitioning the considered frame into many coding units
(region) where each unit is encoded differently. This partitioning is, however, done at
the decoder while generating the side-information and the region map is sent over to
encoder at very little rate penalty. The partitioning allows allocation of appropriate
DVC coding parameters (virtual channel, rate, and quantizer) to each region. The
resulting regions map is compressed by employing quadtree algorithm and
communicated to the encoder via the feedback channel. The rate control in DVC is
performed by channel coding techniques (turbo codes, LDPC, etc.). The performance
of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and
an adaptive WZ DVC is designed both in transform domain and in pixel domain. The
transform domain WZ video coding (TDWZ) has distinct superior performance as
compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the
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spatial redundancy during the encoding. The performance evaluations show that the
proposed system is superior to the existing distributed video coding solutions.
Although the, proposed system requires extra bits representing the "regions map" to be
transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art
frame based DVC by 0.6-1.9 dB.
The feedback channel (FC) has the role to adapt the bit rate to the changing
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statistics between the side infonmation and the frame to be encoded. In the
unidirectional scenario, the encoder must perform the rate control. To correctly
estimate the rate, the encoder must calculate typical side information. However, the
rate cannot be exactly calculated at the encoder, instead it can only be estimated. This
work also prbposes a feedback-free region-based adaptive DVC solution in pixel
domain based on machine learning approach to estimate the side information.
Although the performance evaluations show rate-penalty but it is acceptable
considering the simplicity of the proposed algorithm.
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Improved Wyner-Ziv video coding efficiency using bit plane prediction
The research work is partially funded by STEPS-Malta and partially by the European Union - ESF 1.25.Distributed Video Coding (DVC) is a coding paradigm where video statistics are exploited, partially or totally, at the decoder. The performance of such a codec depends on the accuracy of the soft-input information estimated at the decoder, which is affected by the quality of the side information (SI) and the dependency model. This paper studies the discrepancies between the bit planes of the Wyner-Ziv (WZ) frames and the corresponding bit planes of the SI. The relationship between these discrepancies is then exploited to predict the locations where the bit plane of the SI is expected to differ from that of the original WZ frame. This information is then used to derive more accurate soft-input values that achieve better compression efficiencies. Simulation results demonstrate that a WZ bit-rate reduction of 9.4% is achieved for a given video quality.peer-reviewe
Video Compression for Camera Networks: A Distributed Approach
The problem of finding efficient communications techniques to distribute multi-view video content across different devices and users in a network is receiving a great attention in the last years. Much interest in particular has been devoted recently to the so called field of Distributed Video Coding (DVC). After briefly reporting traditional approaches to multiview coding, this chapter will introduce the field of DVC for multi-camera systems. The theoretical background of Distributed Source Coding (DSC) is first concisely presented
and the problem of the application of DSC principles to the case of video sources is then analyzed. The topic is presented discussing approaches to the problem of DVC in both
single-view and in multi-view applications
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